The statistics below come from the first systematic strategy developed with Judge Research's software stack. We are currently working on the code base needed to go live with test capital.
The strategy is a long-short strategy that holds positions in BTC & ETH spot & perps for time periods of 15 minutes - 1 hour. It is designed to have close to zero correlation with the market over the long run.
Figures are refreshed on a daily basis, with enough delay they cannot be used by others. All the data below comes from after the models were fit & the strategy designed. Slippage + fees are assumed to be 0.2%.
| Start | End | Duration | Exposure | n Pos. | Mean Hold Time | Ret. Summed | Cumulative | Annualized | Buy & Hold | Sharpe | Sortino | Win % | W/Out Slip. | Max Drawdown | M.D. Duration |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-11-17 06:45 | 2022-12-14 04:30 | 26 days 21:45 | 7.25% | 139 | 0 days 00:20 | 18.84% | 21.12% | 622.01% | 9.27% | 4.81 | 5.48 | 58.27% | 76.26% | -4.6% | 5 days 16:12 |
If a strategy is profitable only with very particular settings, it is more likely to be overfit. Ideally one would see a smooth, concave distribution over a space of reasonable parameter values.
Rotate the figure and zoom in to explore the distribution of our strategy's profitability over where we set our take-action thresholds.
Notice that the profitability of the strategy presented here is much lower than could be achieved by other combinations of thresholds.
Backtest.optimize: 0%| | 0/75 [00:00<?, ?it/s]